Mutational Mosaicism in Breast Cancer

In recent years, a huge number of mutational variants had been identified in breast cancer by next-generation sequencing technologies. Even though a considerable portion of them are variants with low variant allele fraction (<30%), which could give rise to suspicion among us regarding whether they might be false or true, recent pioneering studies have begun to corroborate that a certain amount of them are true variants associated with mutational mosaicism. In this study, for the first time, we present pathogenic mutational mosaicism in breast cancer by carrying out comprehensive analysis of large-scale somatic mutation databases far beyond a limited scale of individual cohorts. We identified 23 pathogenic and likely pathogenic mutations with low variant allele fraction (≤ 30%). Of them, there are 8 TP53, 3 PIK3CA, 2 KRAS and 2 GNAS mutations, and one each of SLC25A19, OTC, PACS1, FLG, NCF4, UROS, MLC1, and LTBP2 mutations. For 9 of the mosaic mutations, their variant allele fractions are more than 50% in clinical breast cancer samples compared with those in the normal blood samples, suggesting their contribution to predisposition for carcinogenesis. Three TP53 mosaic mutations (pY220S, p.R273C and p.V272M), and UROS p.L4F could affect directly or indirectly post-translational modifications (phosphorylation, methylation and acetylation). In addition, our protein structural analysis revealed that 4 pathogenic mosaic mutations (p.S241C, p.R273C and p.R248W in p53, and PIK3CA p.E545K) could reside on contact surfaces for protein-protein interactions, consequently affecting the interactions essential for DNA repair pathway. Recurrence free survival analysis showed that expression level of the genes associated with mosaic mutations could be significantly related with patients’ survival. Furthermore, our analysis of somatic variant databases revealed that the 23 pathogenic mosaic mutations might make pivotal contribution to predisposition for carcinogenesis in not only breast cancer but also diverse other cancer types. Taken together, our result presents pathogenic mosaic mutations associated with breast cancer predisposition, which will help clinicians, clinical oncologists and tumor biologists predict breast cancer predisposition, diagnose breast carcinogenesis, choose therapeutic treatment options and elucidate oncogenic mechanisms in the upcoming years.